Zexin Li

Zexin Li

Ph.D. Student of ECE

The University of California, Riverside

Biography

I am a Ph.D. student at the University of California, Riverside (UCR). I am fortunate to be advised by Dr. Cong Liu . I received a bachelor’s degree from the Southern University of Science and Technology (SUSTech) under the advice of Dr. Yuqun Zhang in July 2020. My research interests lie in interdisciplinary fields of real-time embedded systems and on-device machine learning.

I am actively looking for cooperation in the following topics: (1) deploying machine learning models on real-time embedded devices, (2) system-application co-optimization of machine learning systems, and (3) improving performance robustness in machine learning systems.

Feel free to contact me if we share common research interests.

Download my Curriculum Vitae .

Interests
  • Real-time Embedded System
  • On-device Machine Learning
  • Self-adaptive System
  • Efficient Machine Learning
Education

  • Ph.D. Candidate, 2022 - Now

    The University of California, Riverside

  • Ph.D. Candidate, 2020 - 2022

    The University of Texas at Dallas

  • B.S., 2016 - 2020

    Southern University of Science and Technology

News

08/2024 - One paper is accepted by IEEE Signal Processing Letters .
07/2023 - Two papers are accepted by RTSS'24 .
04/2024 - One paper is accepted by FSE'24 .
03/2024 - Pass the qualification exam of Ph.D. at UCR .
07/2023 - Three papers are accepted by RTSS'23 .
06/2023 - One paper is accepted by IROS'23 .
05/2023 - Two papers are accepted by ACL'23 .
02/2023 - One paper is accepted by CVPR'23 .
09/2022 - Honored to receive the Dean’s Distinguished Fellowship, UCR.
09/2022 - Join UCRiverside and Dr. Cong Liu ’s Autonomous Embedded Systems Lab in 2022 Fall.
01/2022 - Pass the qualification exam of Ph.D. at UTDallas .
01/2022 - Join UTDallas and Dr. Cong Liu ’s Real-Time System Lab in 2022 Spring.
05/2021 - Begin the research intern in Tecent Youtu Lab , Shanghai, China.
04/2021 - Admitted into Tencent Rhino Bird Elite Talent Training Program .
03/2021 - One paper is accepted by JSA , great thanks to Dr. Yuqun Zhang .
10/2019 - Begin the research intern in Kuaishou , Shenzhen, China.

Publications

Ziliang Zhang, Zexin Li, Hyoseung Kim, Cong Liu (2024). BOXR: Body and head motion Optimization framework for eXtended Reality. In RTSS'24.

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Soheil Shirvani, Aritra Samanta, Zexin Li, Cong Liu (2024). DuoJoule: Accurate On-Device Deep Reinforcement Learning for Energy and Timeliness. In RTSS'24.

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Xiaoxue Gao, Zexin Li, Yiming Chen, Cong Liu, Haizhou Li (2024). Transferable Adversarial Attacks against ASR. In IEEE SPL.

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Simin Chen, Zexin Li, Wei Yang, Cong Liu (2024). DeciX: Explain Deep Learning Based Code Generation Applications. In FSE'24.

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Zexin Li, Soroush Bateni, Cong Liu (2024). Genie: Smart ROS-based Caching for Connected Autonomous Robots. In Arxiv.

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Yufei Li, Zexin Li, Wei Yang, Cong Liu (2023). RT-LM: Uncertainty-Aware Resource Management for Real-Time On-Device Language Models. In RTSS'23.

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Zexin Li, Aritra Samanta, Yufei Li, Andrea Soltoggio, Hyoseung Kim, Cong Liu (2023). R^3: On-device Real-Time Deep Reinforcement Learning for Autonomous Robotics. In RTSS'23.

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Zexin Li, Tao Ren, Xiaoxi He, Cong Liu (2023). RED: A Systematic Real-Time Scheduling Approach for Robotic Environmental Dynamics. In RTSS'23.

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Zexin Li, Xiaoxi He, Yufei Li, Wei Yang, Lothar Thiele, Cong Liu (2023). MIMONet: Multi-Input Multi-Output On-Device Deep Learning. In Arxiv.

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Shahab Nikkhoo, Zexin Li, Aritra Samanta, Yufei Li, Cong Liu (2023). PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas. In IROS'23.

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Yiming Chen, Simin Chen, Zexin Li, Wei Yang, Cong Liu, Robby Tan, Haizhou Li (2023). Dynamic Transformers Provide a False Sense of Efficiency. In ACL'23.

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Yufei Li, Zexin Li, Yingfan Gao, Cong Liu (2023). White-Box Multi-Objective Adversarial Attack on Dialogue Generation. In ACL'23.

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Zexin Li*, Bangjie Yin, Taiping Yao, Junfeng Guo, Shouhong Ding, Simin Chen, Cong Liu (2023). Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition. In CVPR'23.

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Zexin Li, Yuqun Zhang*, Ao Ding, Husheng Zhou, Cong Liu (2021). Efficient algorithms for task mapping on heterogeneous CPU/GPU platforms for fast completion time. In JSA.

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